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General Information
    • ISSN: 2010-3751
    • Frequency: Bimonthly (2012-2016); Quarterly (Since 2017)
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Mohamed Othman
    • Executive Editor: Ms. Nancy Y. Liu
    • Abstracting/ Indexing: Google Scholar, Engineering & Technology Digital Library, and Crossref, DOAJ, Electronic Journals LibraryEI (INSPEC, IET).
    • E-mail:  ijfcc@ejournal.net 
Editor-in-chief
Prof. Mohamed Othman
Department of Communication Technology and Network Universiti Putra Malaysia, Malaysia
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.
IJFCC 2013 Vol.3(1): 60-65 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2014.V3.268

Malaria Incidence Forecasting from Incidence Record and Weather Pattern Using Polynomial Neural Network

Anditya Arifianto, Ari Moesriami Barmawi, and Agung Toto Wibowo
Abstract—Malaria affects over 100 million persons worldwide with approximately 2,414 deaths a day in average each year. Indonesia is on the third highest position in the number of malaria incident in South East Asia, with 229,819 confirmed cases and 432 deaths only at 2010. Previous work has demonstrated the potential of neural networks in predicting the behavior of complex, non-linear systems. GMDH Polynomial Neural Network was applied in a great variety of areas for data mining and knowledge discovery, forecasting, systems modeling, optimization, and pattern recognition. Study has also shown the close relation between Malaria incidence and weather pattern. This paper proposed a modified GMDH Polynomial Neural Network to reduce the learning time and computation while maintaining the accuracy in predicting Malaria incidence by relating it to weather pattern. Based on the experiments, it was proven that the modified GMDH PNN was able to reduce the learning time by 72% and improve the accuracy into 88.02% compared to the original GMDH PNN.

Index Terms—Malaria, prediction, weather pattern, polynomial neural network.

The authors are with Graduate School of Informatics Engineering, Telkom Institute of Technology, Bandung, Indonesia (e-mail: anditya.arifianto@yahoo.com, mbarmawi@melsa.net.id, agungtotowibowo@yahoo.com).

[PDF]

Cite:Anditya Arifianto, Ari Moesriami Barmawi, and Agung Toto Wibowo, "Malaria Incidence Forecasting from Incidence Record and Weather Pattern Using Polynomial Neural Network," International Journal of Future Computer and Communication vol. 2, no. 6, pp. 60-65, 2014.

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